Jornal de Ciência da Computação e Biologia de Sistemas

A full description of a high-level language for solving arbitrary problems in heterogeneous, distributed and dynamic worlds, both physical and virtual, will be presented and discussed. The language is based on holistic and gestalt principles representing semantic level solutions in distributed environments in the form of self-evolving patterns. The latter are covering, grasping and matching the distributed spaces while creating active distributed infrastructures in them operating in a global-goal-driven manner but without traditional central resources. Taking into account the existing sufficient publications on the approach developed, the paper will be showing only elementary examples using the Spatial Grasp Language and key ideas of its networked implementation.

The presentation describes organization of large distributed robotized systems with the help of high level networking ideology and technology allowing for integral, holistic solutions of complex problems in rapidly changing and unpredictable environments. Exemplary scenarios in Spatial Grasp Language for practical tasks oriented on the use of multiple cooperative robotic units operating under unified control provided by the technology are also exhibited and discussed.

Background: Currently, diabetes mellitus, specifically, Type 2 diabetes is a multifactorial metabolic disorder that affects more than 348 million people worldwide. It is considered to be one of the main causes of mortality. The pathway of type 2 diabetes is characterized both by insulin resistance in muscle, fat, and liver and a relative failure of the pancreatic β cell. Despite extensive study, yet no unifying hypothesis exists to explain these defects and the proper treatment. The key goal of diabetes treatment is to prevent complications because over time, diabetes can damage the heart, blood vessels, eyes, kidneys, and nerves. Therefore there is a great need to develop new and effective therapies for treating diabetic complications early before it cause irreparable tissue damage. Recently, advances experimental evidence empowers the idea that diabetic patients may greatly benefit from cell-based therapies, which include the use of adult stem and/or progenitor cells in disease therapy. In particular, therapeutic effect of bone marrow stem cell in treating the type 2 diabetic patients. Motivation: Mesenchymal stem cells (MSCs) are adherent and pluripotent and non-hematopoietic progenitor cells. Human bone marrow MSCs have been shown to inhibit antigen-dependent CD4+ and CD8+ T cell proliferation in an allogeneic setting in vitro. They have been found to reside in most organs and tissues investigated to date, including bone marrow, adipose, dermis, muscular tissue, hair follicles, the periodontal ligament and the placenta. In addition, recent studies have shown that adult bone marrow stem cells can differentiate into several types such as blood, liver, lung, skin, muscle, neuron and insulin producing cells. This has motivated us to explore potentials of their therapeutic applications in treating diabetes mellitus or type-2 diabetes. This article proposes a novel mechanism to isolate adult rat bone marrow stem cells and test their ability to treat diabetic rats. The main focus of this research is to investigate the therapeutic effect of mesenchymal stem cells on the diabetic rats. Experimental methods, data and results: The experimental studies were carried out based on twelveweek old healthy Sprague Dawley (S.D) rats and it was used for isolation and transplantation of stem cells. We carried a total number of 40 Sprague Dawley (S.D) male rats; 12-14 weeks old age and weighting 180-250 gm were used in the experimental study. Rats were obtained from Animal House of Nile Center for Experimental Researches, Mansoura, Egypt. Animals were housed in separate metal cages, fresh and clean drinking water was supplied adlibtium through specific nipple. The animals were anesthetized by halothane, and then the skin was sterilized with 70% ethyl alcohol before cutting the skin. The femurs and tibia were carefully dissected from adherent soft tissues. Then they were placed into sterilized beaker containing 70% ethyl alcohol for 1-2 min. The bones were put in Petri dish contain Phosphate buffer saline 1X (PBS) (Hyclone, USA) for wash. The bones were taken to laminar air flow (unilab biological safety cabinet class II, china) to extract the BM. The two ends of the bones were removed using sterile scissors. Conclusion and future work: Currently, the obtained results revealed that diabetes caused bad effects on the blood picture, pancreas and kidney functions, as well as the immune system represented by TNF. Treatment the diabetic rats by MSCs engrafting improved the tested parameters towards the stats of normal case. Nevertheless, the wide application of the stem cells engrafting still needs more investigations to be assured.

Data mining has pushed the realm of information technology beyond predictable limits. Data mining has left its permanent marks on decision making in just in few years of its inception. Missing value is one of the major factor, which can render the obtain result beyond use attained from specific data set by applying data mining technique. There could be numerous reasons for missing values in a data set such as human error, hardware malfunction etc. It is imperative to tackle the labyrinth of missing values before applying any technique of data mining; otherwise, the information extracted from data set containing missing values will lead to the path of wrong decision making. There are several techniques available to control the issue of missing values such as replacing the missing value with: (a) closest value, (b) mean value and (c) median value etc. Some algorithms are also used to deal with the problem of missing values such as k-nearest neighbour. Paper reviewed certain techniques and algorithms to deal with the puzzle of missing values whereby achieving pure data set (i.e., data set without missing value) which in-turn will lead to path of correct and accurate decision making.

This paper presents a new hybridized genetic algorithm for optimization of a function with several variables. To construct the proposed algorithm, a new operator by the name of chemotactic operator has been constructed using the chemotaxis behaviour of the E. coli bacteria. Then this integrated genetic algorithm has been used to obtain minimum optimal of a single objective function. Finally, some numeric simulations have been carried out to show the effectiveness of the proposed algorithm comparing the results of simple genetic algorithm using some benchmark functions.

In order to develop an easier and more inexpensive tool than using MEG and fMRI for diagnosing neurological diseases such as AD and FTD and checking their prognoses in future, we constructed scalp-recorded-EEGbased brain functional connectivity networks (BFCNs), and preliminarily compared Alzheimer’s disease (AD) and frontotemporal dementia (FTD) patients, their prognoses and control subjects by the BFCNs. The present comparison among AD, FTD and older controls roughly supported the previous findings for synchronization likelihood values, unweighted graphs, clustering coefficient and characteristic path length. However, there were reverse differences in small-worldness. For AD and FTD, there were several electrode positions with higher betweenness centrality than the older controls. It might be suggested that we should investigate the betweenness centrality in more details.

The use of mobile devices is increasingly on the rise in our daily lives and many information is exchanged and stored on these devices. Thus, there are some risks that must be prevented as information leakage, installing malicious files one of the techniques used in the safety process is the encryption that through it, the cryptographic keys are created, ensuring a high level of protection the information. Soon this work comes with the proposal to show the development of an application to perform this security function, using the Blowfish algorithm, implemented on the Android platform, enabling the user data encryption of your devices.

The concepts of δ-Ideals and principal δ-Ideals are introduced in an MS-algebra and many properties of these ideals are studied. It is observed that the class of all δ-Ideals forms a complete distributive lattice and the class of all principal δ-Ideals forms a de Morgan algebra. A characterization of δ-Ideals in terms of principal δ-Ideals is given. Finally, many properties of δ-Ideals are studied with respect to homomorphisms.